Digital inclusive finance, industrial structure, and economic growth: An empirical analysis of Beijing-Tianjin-Hebei region in China.

As a product of combining digital technology and traditional finance, digital inclusive finance plays a vital role in economic growth. This paper deeply analyzes the impact of digital inclusive finance on economic growth and the specific transmission path. This research selects the municipal panel data of Beijing-Tianjin-Hebei from 2011 to 2020 and empirically studies the impact of digital inclusive finance on economic growth. From the perspectives of industrial structure transformation speed, industrial structure upgrading, and industrial structure rationalization, this study analyzes the role of industrial structure in the impact of digital inclusive finance on economic growth and tests the heterogeneity of the impact of digital inclusive finance on economic growth. The results show that digital inclusive finance has a significant role in promoting economic growth. The depth of use of digital inclusive finance has the most significant impact, followed by the breadth of coverage, and the degree of digitization is the smallest. The industrial structure transformation speed and the industrial structure rationalization play a significant intermediary role in the economic growth effect of digital inclusive finance, and the industrial structure upgrading has no significant impact on the economic growth effect of digital inclusive finance; the promotion effect of digital inclusive finance on economic growth is bigger in the economically developed group, the higher digital inclusive finance group and the technologically developed group, and the promotion effect is smaller in the economically underdeveloped group, the lower digital inclusive finance group and the technologically underdeveloped group. The results provide a strong reference for policy formulation to promote the development of digital inclusive finance and economic growth.

Prognostic Assessment of Colorectal Cancer Patients after Laparoscopic Surgery: A Comprehensive Evaluation of the Glasgow Prognostic Score and Fibrinogen-to-Prealbumin Ratio.

BACKGROUND Previous studies have shown that systemic inflammation and suboptimal nutritional status are associated with poor cancer prognosis. This study aims to investigate the prognostic value of preoperative Glasgow prognostic score (GPS) and fibrinogen-to-prealbumin ratio (FPR) in patients with CRC (colorectal cancer) after laparoscopic surgery. MATERIAL AND METHODS In this study, the clinical data of 112 patients with CRC who underwent laparoscopic surgery were retrospectively analyzed, and the 3-year and 5-year survival rates of these patients were evaluated. In addition, the prognostic role of preoperative FPR and GPS in CRC patients was assessed using X-tile software, Kaplan-Meier analysis, and Cox regression analysis. Receiver operating characteristic (ROC) curves were generated to assess the predictive value of FPR, GPS, and FPR-GPS for the survival of these patients. RESULTS The results revealed a significant negative correlation between high FPR, elevated GPS, and overall survival (OS) in patients with CRC. Univariate and multivariate Cox regression analyses identified GPS (HR=3.207, 95% CI: 1.746~6.126), FPR (HR=2.669, 95% CI: 1.052~6.772), and lymph node metastasis (HR=2.222, 95% CI: 1.199~4.115) as independent prognostic indicators for overall survival. The ROC analysis demonstrated that the prediction based on FPR and GPS outperformed a single indicator in accurately predicting the prognosis of CRC patients. CONCLUSIONS Combining the preoperative FPR with the GPS contributes to accurate prognosis assessment for CRC patients after laparoscopic surgery. Patients exhibiting high FPR and GPS values are associated with a worse prognosis.

Risk assessment of trace metals and polycyclic aromatic hydrocarbons in seawater of typical bays in the Bohai Sea.

The ecological risks of trace metals (Cu, Zn, As, Cd, Pb, and Hg) and PAHs in seawater from three typical bays of the Bohai Sea (the Liaodong Bay, Bohai Bay, and Laizhou Bay) were comprehensively assessed by recompiling 637 sites. Results highlighted that scrutiny should be given to the ecological risks of Cu (3.80 µg/L) in the Bohai Bay and Hg (0.23 µg/L) in the Laizhou Bay. Conversely, the Liaodong Bay exhibited negligible ecological risks related to trace metals. The risks of ΣPAHs in the Liaodong Bay, Bohai Bay, and Laizhou Bay were moderate, with mean concentrations of 368.16 ng/L, 731.93 ng/L, and 187.58 ng/L, respectively. The source allocation of trace metals and PAHs required consideration of spatial variability and anthropogenic factors, which greatly affected the distribution and composition of these pollutants. The combined ecological risks in the Bohai Bay (6.80 %) and Laizhou Bay (5.43 %) deserved more attention.

Assessment of Keratoconus Risk in Very Asymmetric Ectasia Using Corneal Tomographic and Biomechanical Parameters.

Purpose: To investigate the relationship between corneal tomographic or biomechanical parameters and risk of keratoconus in very asymmetric ectasia (VAE). Methods: This retrospective case-control single-centre study included patients with VAE and normal controls. The VAE group had clinical ectasia in one eye and normal topography (VAE-NT) in the fellow eye; VAE-NT eyes were selected for analysis. The control group was selected from corneal refractive surgery candidates; the right eye was enrolled. Scheimpflug-based corneal tomography (Pentacam) and corneal biomechanical assessment (Corvis ST) were performed. Univariate and multivariable logistic regression were performed using Cox proportional hazards models to evaluate keratoconus-associated risk factors. A two-piecewise linear regression model was applied to examine the threshold effect of selected vital paragmeters on the risk of keratoconus according to a smoothing plot. Results: Threshold effect between tomographic integration and risk of keratoconus was observed. Discrepancy between the central corneal thickness and thinnest corneal thickness (discrepancy CCT vs TCT) greater than 5 µm, discrepancy between the apex corneal thickness and thinnest corneal thickness (discrepancy ACT vs TCT) greater than 3 µm, vector distance between CCT and TCT (distance CCT vs TCT) greater than 0.65 mm indicated a significant increased risk of keratoconus. Risk of keratoconus decreased when distance CCT vs TCT was less than 0.65 mm. Conclusion: Discrepancy CCT vs TCT, discrepancy ACT vs TCT, and distance CCT vs TCT can be used as indicators for risk assessment of early keratoconus.

Causality assessment of circulating Vitamin D level on venous thromboembolism: A Mendelian randomization study.

BACKGROUND AND AIMS: The associations of vitamin D level with venous thromboembolism (VTE) reported in observational studies, whereas these causal associations were uncertain in European population. Therefore, we used Mendelian randomization (MR) method to explore the causal associations between 25-hydroxyvitamin D (25(OH)D) concentrations and the risk of VTE and its subtypes [including deep vein thrombosis (DVT) and pulmonary embolism (PE)]. METHODS AND RESULTS: We used three kinds of genetic instruments to proxy the exposure of 25(OH)D, including genetic variants significantly associated with 25(OH)D, expression quantitative trait loci of 25(OH)D target genes, and genetic variants within or nearby 25(OH)D target genes. MR analyses did not provide any evidence for the associations of 25(OH)D levels with VTE and its subtypes (p > 0.05). The summary-data-based MR (SMR) analyses indicated that elevated expression of VDR was associated with decreased risk of VTE (OR = 0.81; 95% CI, 0.65-0.998; p = 0.047) and PE (OR = 0.67; 95% CI, 0.50-0.91; p = 0.011), and expression of AMDHD1 was associated with PE (OR = 0.93; 95% CI, 0.88-0.99; p = 0.027). MR analysis provided a significant causal effect of 25(OH)D level mediated by gene AMDHD1 on PE risk (OR = 0.09; 95% CI, 0.01-0.60; p = 0.012). CONCLUSION: Our MR analysis did not support causal association of 25(OH)D level with the risk of VTE and its subtypes. In addition, the expression of VDR and AMDHD1 involved in vitamin D metabolism showed a strong association with VTE or PE and might represent targets for these conditions.

The Societal Cost of Schizophrenia: An Updated Systematic Review of Cost-of-Illness Studies.

BACKGROUND: Schizophrenia imposes a substantial economic burden on society. This updated systematic review aims to collate the latest societal cost of schizophrenia across countries by reviewing recent cost-of-illness (COI) studies. METHODS: An electronic search was conducted across several databases (MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Health Management Information Consortium, and System for Information on Grey Literature) to identify COI studies published from 2016 to 2022. Two independent reviewers selected studies for inclusion. The cost components and estimates reported by included studies were descriptively summarised. All costs were converted to US dollars (2022 values). Study quality was assessed using a checklist adapted from Larg & Moss. RESULTS: Twenty-four studies were included (5 from the update review and 19 from the original review), of which only two were conducted for low- and middle-income countries (LMICs). Widespread methodological heterogeneity among included studies was observed. The annual societal cost per person varied from US$819 in Nigeria to US$94,587 in Norway. Productivity losses accounted for 32-83% of the overall societal cost, whilst direct healthcare cost made up 11-87%. The reporting quality of included studies varied. CONCLUSION: This review highlights the substantial economic burden of schizophrenia and a lack of COI studies for LMICs. Recommendations on future research, and good practices on improving the methodological and reporting quality of COI research for schizophrenia are provided.

A biosensing system employing nonlinear dynamic analysis-assisted neural network for drug-induced cardiotoxicity assessment.

Preclinical investigation of drug-induced cardiotoxicity is of importance for drug development. To evaluate such cardiotoxicity, in vitro high-throughput interdigitated electrode-based recording of cardiomyocytes mechanical beating is widely used. To automatically analyze the features from the beating signals for drug-induced cardiotoxicity assessment, artificial neural network analysis is conventionally employed and signals are segmented into cycles and feature points are located in the cycles. However, signal segmentation and location of feature points for different signal shapes require design of specific algorithms. Consequently, this may lower the efficiency of research and the applications of such algorithms in signals with different morphologies are limited. Here, we present a biosensing system that employs nonlinear dynamic analysis-assisted neural network (NDANN) to avoid the signal segmentation process and directly extract features from beating signal time series. By processing beating time series with fixed time duration to avoid the signal segmentation process, this NDANN-based biosensing system can identify drug-induced cardiotoxicity with accuracy over 0.99. The individual drugs were classified with high accuracies over 0.94 and drug-induced cardiotoxicity levels were accurately predicted. We also evaluated the generalization performance of the NDANN-based biosensing system in assessing drug-induced cardiotoxicity through an independent dataset. This system achieved accuracy of 0.85-0.95 for different drug concentrations in identification of drug-induced cardiotoxicity. This result demonstrates that our NDANN-based biosensing system has the capacity of screening newly developed drugs, which is crucial in practical applications. This NDANN-based biosensing system can work as a new screening platform for drug-induced cardiotoxicity and improve the efficiency of bio-signal processing.

Needs and views on healthy lifestyles for the prevention of dementia and the potential role for mobile health (mHealth) interventions in China: a qualitative study.

OBJECTIVES: Over the coming decades, China is expected to face the largest worldwide increase in dementia incidence. Mobile health (mHealth) may improve the accessibility of dementia prevention strategies, targeting lifestyle-related risk factors. Our aim is to explore the needs and views of Chinese older adults regarding healthy lifestyles to prevent cardiovascular disease (CVD) and dementia through mHealth, supporting the Prevention of Dementia using Mobile Phone Applications (PRODEMOS) study. DESIGN: Qualitative semi-structured interview study, using thematic analysis. SETTING: Primary and secondary care in Beijing and Tai'an, China. PARTICIPANTS: Older adults aged 55 and over without dementia with an increased dementia risk, possessing a smartphone. Participants were recruited through seven hospitals participating in the PRODEMOS study, purposively sampled on age, sex, living area and history of CVD and diabetes. RESULTS: We performed 26 interviews with participants aged 55-86 years. Three main themes were identified: valuing a healthy lifestyle, sociocultural expectations and need for guidance. First, following a healthy lifestyle was generally deemed important. In addition to generic healthy behaviours, participants regarded certain specific Chinese lifestyle practices as important to prevent disease. Second, the sociocultural context played a crucial role, as an important motive to avoid disease was to limit the care burden put on family members. However, time-consuming family obligations and other social values could also impede healthy behaviours such as regular physical activity. Finally, there seemed to be a need for reliable and personalised lifestyle advice and for guidance from a health professional. CONCLUSIONS: The Chinese older adults included in this study highly value a healthy lifestyle. They express a need for personalised lifestyle support in order to adopt healthy behaviours. Potentially, the PRODEMOS mHealth intervention can meet these needs through blended lifestyle support to improve risk factors for dementia and CVD. TRIAL REGISTRATION NUMBER: ISRCTN15986016; Pre-results.

Quantitative assessment of the risk of human activities on landscape fragmentation: A case study of Northeast China Tiger and Leopard National Park.

Risk assessment of human activities on landscape fragmentation in nature reserves can effectively balance the conflict between wildlife conservation and human development. However, previous studies had been unable to quantitatively assess the risk of human activities on landscape fragmentation. Thus, we constructed a risk assessment methodology to quantitatively assess the risk of different human activities on the Landscape Fragmentation Composite Index (LFCI) in the Northeast China Tiger and Leopard National Park (NCTLNP). First, we fitted the relationship curve between LFCI and different human activity factors based on the Generalized Additive Model (GAM) to determine the impact patterns of each factor on LFCI. Secondly, we identified impact risk areas of each human activity factor on LFCI by the location of threshold points in the curve and analyzed their spatiotemporal variation characteristics from 2015 to 2020. The results show that the relationship between LFCI and Land Use Intensity (LUI) showed an inverted "U" shape, the relationship with Population Density (POPD) showed a "rising-flat-rising" trend, and the relationship with Traffic Accessibility (TA) and Industrial and Mining Activity (IMA) showed a positive correlation after a flat interval. In addition, we found that the LUI and IMA impact risk areas were widely distributed and remained stable for five years. But the POPD impact risk area was mainly distributed around settlements and expanded by 6.6 % from 2015 to 2020. The TA impact risk area was distributed in strips and expanded by 16.38 % from 2015 to 2017 due to the construction of the G331 national road. And the joint impact risk area of these four factors expanded by 1.55 times in five years. Our research can provide a reference for ecological risk assessment under the impact of human activities on other nature reserves in the world.

Exploring teachers' attitudes and self-efficacy beliefs for implementing student self-assessment of English as a foreign language writing.

With the growing need to nurture students' independent learning, English language teaching (ELT) practices should reflect student-centered assessment approaches, such as self-assessment, an ultimate goal of higher education. It has been pointed out that to conduct effective self-assessment, students need to be taught systematically, and that is where teachers are expected to step in. Prior to implementing such a change in ELT, it is important to conduct research on English as a foreign language (EFL) teachers' attitudes toward, and self-efficacy beliefs about, implementing self-assessment to cultivate capable student self-assessors. Although the strong global endorsement of self-assessment over the past two decades has witnessed its classroom implementation in different disciplines, such studies are scant in relation to EFL writing classrooms. To address this gap, the present qualitative research examined five Chinese tertiary EFL writing teachers' attitudes toward and self-efficacy beliefs about student self-assessment of writing, as well as possible reasons that discourage them from engaging students in self-assessment practices. Data collected from in-depth, semi-structured interviews indicated that self-assessment, a critical element of self-regulated learning, is surprisingly missing from the teachers' knowledge base and previous practices. Additionally, the findings offer insights into the striking differences in teachers' understanding of, attitudes toward, and low self-efficacy beliefs about self-assessment of writing. Reasons why teachers choose not to implement self-assessment of writing are also discussed. Findings from this study contribute to a deeper understanding of how EFL teachers' attitudes and self-efficacy beliefs are enacted in relation to their classroom assessment practices in order to move forward discussions on the feasibility of implementing self-assessment of writing in tertiary EFL classrooms.

Assessment of the Causal Effect of IgG N-Glycosylation Level on Risk of Dementia: A 2-Sample Mendelian Randomization Study.

BACKGROUND: Previous prospective studies highlighted aberrant immunoglobulin G (IgG) N-glycosylation as a risk factor for dementia [such as Alzheimer's disease (AD) and vascular dementia (VaD)]. It is unclear whether this association is causal or explained by confounding or reverse causation. OBJECTIVE: The aim is to examine the association of genetically predicted IgG N-glycosylation with dementia using 2-sample Mendelian randomization (MR). METHODS: Independent genetic variants for IgG N-glycosylation traits were selected as instrument variables from published genome-wide association studies (GWAS) among individuals of European ancestry. We extracted their corresponding summary statistics from large-scale clinically diagnosed AD GWAS dataset and FinnGen biobank VaD GWAS dataset. The inverse variance weighted (IVW) was performed to calculate the effect estimates. Meanwhile, multiple sensitivity analyses were used to assess horizontal pleiotropy and outliers. RESULTS: There were no associations of genetically predicted IgG N-glycosylation traits with the risk of AD and VaD using the IVW method (all Bonferroni corrected p > 0.0013). These estimates of four additional sensitivity analyses methods were consistent with the IVW estimates in terms of direction and magnitude. Additionally, the MR-PRESSO global test and the intercept of MR-Egger regression indicated no evidence of horizontal pleiotropy. Meanwhile, the heterogeneity test showed no significant heterogeneity using the Cochran Q statistic. The leave-one-out sensitivity analyses also did not detect any significant change. CONCLUSION: Our MR study did not support evidence for the hypothesis that IgG N-glycosylation level may be causally associated with the risk of dementia.

Cryptocurrency price discrepancies under uncertainty: Evidence from COVID-19 and lockdown nexus.

The past decades have witnessed recurrent price discrepancies in cryptocurrency markets across countries. In addition to prior explanations that generally attribute this phenomenon to domestic capital controls during normal periods, we provide another explanation that investors perceive cryptocurrency as an alternative (hedging) investment, especially under uncertainty. Using the emerging of the COVID-19 pandemic in 2020 and the subsequent lockdown policies implemented by a group of countries as natural experiments, we adopt a difference-in-difference framework to examine how the nexus affects Bitcoin price discrepancies. We find that price discrepancies are larger in countries with confirmed cases of COVID-19 and rigorously implementing lockdown policies. We then verify our "alternative investment" hypothesis on the mechanism by showing that countries with intensified exposure to media hype on COVID-19 topics and with more panic emotion among citizens during the pandemic generally experienced larger Bitcoin price discrepancies than their counterparts. We also find that domestic capital control, sanitary policy stringency, uncertainty aversion, individualistic culture, and governmental power could moderate the general effect.

Synchronization of Neural Networks Involving Distributed-Delay Coupling: A Distributed-Delay Differential Inequalities Approach.

In this article, we address the synchronization issue for coupled neural networks (CNNs) with mixed couplings by way of the delayed impulsive control, where the delay is distributed. Particularly, mixed couplings comprise the current-state coupling and the distributed-delay coupling, where influences on network connections caused by the past information of CNNs over a certain period are considered. First, we propose a novel array of delayed impulsive differential inequalities involving distributed-delay-dependent impulses, where distributed delays can be relatively larger. Second, we apply such delayed inequalities to analyze the problem of synchronization for CNNs with two different topologies. Sufficient criteria and distributed-delay-dependent impulsive controller are derived thereby. Furthermore, using techniques of matrix decomposition, several low-dimensional criteria are set out, which are appropriate for applications of large scale CNNs. Finally, a numerical example of CNNs with both the current-state coupling and the distributed-delay coupling involving three cases, are exhibited to exemplify the validity and the efficiency of the obtained theoretical results.

Assessment of Eutrophication and DOC Sources Tracing in the Sea Area around Dajin Island Using CASI and MODIS Images Coupled with CDOM Optical Properties.

The sea area around Dajin Island in the Pearl River Estuary is the second-largest habitat in China for the Indo-Pacific humpback dolphin (Sousa Chinensis). However, the rapid economic development of this area brings potential threats to the aquatic ecology around Dajin Island. Real-time monitoring and evaluation of the ecological health of the sea area are urgent. In this study, band ratio and single-band inversion algorithms were performed to obtain Chlorophyll-a (Chl-a) and Suspended Sediment Concentration (SSC), relying on both Compact Airborne Spectrographic Imager (CASI) and Moderate resolution Imaging Spectrometer (MODIS) images. The CASI/Chl-a with high spatial resolution was adopted to assess the eutrophication status, while the dissolved organic carbon (DOC) concentration and chromophoric dissolved organic matter (CDOM) optical properties were used to derive the material composition and sources. The results suggest that the study area is under a low to medium eutrophication state with evenly distributed low Chl-a concentration. However, higher Chl-a is observed in the outer estuary with MODIS/Chl-a. The relatively high DOC concentration, especially in the north, where aquaculture is practiced, and near the estuary's main axis, i.e., east Dajin Island, indicates that the eutrophication state might be underestimated using satellite chlorophyll alone. CDOM optical properties indicated that terrestrial materials are the DOC's primary material sources, but the DOC derived from fishery aquaculture cannot be ignored. The low Chl-a concentration is likely due to the turbulent hydrodynamic regime caused by jet flow and reciprocating flow in this marine area. Comprehensive observation, including the assessment of different technological platforms, is suggested for the aquatic environment.

Have traffic restrictions improved air quality? A shock from COVID-19.

With the outbreak of COVID-19 (Corona Virus Disease, 2019), China adopted traffic restrictions to reduce the spread of COVID-19. Using daily data before and after the outbreak of COVID-19, an exogenous shock, this paper analyzes the effects of private vehicle restriction policies on air pollution. We find that the private vehicle restriction policies reduce the degree of air pollution to a certain extent. However, their effect varies with other policies implemented in the same period and the economic development of the city itself. Through the analysis of different categories of restrictions, we find that restriction policy for local fuel vehicles and the restriction policy based on the last digit of license plate numbers have the best effect in reducing air pollution. Under the background of COVID-19 epidemic and the implementation of private vehicle restriction policies and other traffic control policies during this period, we have also obtained other enlightenment on air pollution control.

Have driving restrictions reduced air pollution: evidence from prefecture-level cities of China.

With rapid economic development, air pollution became a serious problem in China. Vehicle's exhaust emissions are among the main sources of air pollution. With samples of 173 prefecture-level cities in China from 2006 to 2016, this paper takes the implementation of driving restrictions as a quasi-natural experiment to examine the relationship between driving restrictions and air quality through the difference-in-differences method based on the propensity score matching. Results indicate that driving restrictions have not improved the air quality in terms of average treatment effect as there is no clear evidence that people turn from private cars to busses or subways. Furthermore, heterogeneous effects of driving restrictions exist across different regions and cities of China. The implementation of driving restrictions has significantly positive impacts on air pollution in the Eastern and Central cities of China, while it has significantly negative effects in non-capital cities. This study implies that the development of local public transportation needs to be taken into account when formulating the policy of driving restrictions.

Risk Assessment and Prediction of Severe or Critical COVID-19 Illness in Older Adults.

PURPOSE: This study is to investigate the risk prediction of severe or critical events of COVID-19 in older adults in China and provide the evidence to support the management of older adults with COVID-19. MATERIALS AND METHODS: The clinical data of older adults with COVID-19 admitted to the Shanghai Public Health Clinical Center during January 20, 2020 to March 16, 2020 were collected. The possible risk factors of severe or critical illness were investigated with Cox proportional hazards (PH) regression models for univariate and multivariate analyses to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). For the prediction indicators, optimum cut-off points were determined by calculating Youden's index. The efficacy of risk prediction of severe or critical illness was examined through the receiver operating characteristic (ROC) curve. RESULTS: A total of 110 older adults with COVID-19 were included, in which 21 (19.1%) patients had severe or critical illness of COVID-19. Multivariable regression analysis showed that CD4 cells and D-dimer were independent risk factors. D-dimer, CD4 cells, and CD cells/D-dimer ratio with cut-off values of 0.65 (mg/L), 268 (cell/µL) and 431 were in the prediction of severe or critical illness of older adults with COVID-19. The AUC value of D-dimer, CD4 cells, CD4 cells/D-dimer ratio, the tandem combination and the parallel combination to predict severe or critical illness of the older adults with COVID-19 were 0.703, 0.804, 0.794, 0.812 and 0.694, respectively. CONCLUSION: D-dimer and CD4 cells either by themselves or in combination have demonstrated predictive value in risk stratification as well as established the prognosis of severe or critical illness in older adults with COVID-19.

Predictive value of the sequential organ failure assessment (SOFA) score for prognosis in patients with severe acute ischemic stroke: a retrospective study.

OBJECTIVE: To identify the risk factors for early death and determine the predictive value of the sequential organ failure assessment (SOFA) score for prognosis of severe acute ischemic stroke (AIS). METHODS: A total of 110 patients with severe AIS were enrolled and divided into the non-survivor (n = 34) and survivor groups (n = 76). Logistic regression analysis was conducted to identify risk factors for early death, while the receiver operator characteristic (ROC) curve was used to determine the predictive effect of the SOFA score on prognosis. RESULTS: Logistic regression analysis showed that urinary tract infection (odds ratio [OR] = 17.364, 95% confidence interval [CI]: 1.903-158.427), mechanical ventilation (OR = 1.754, 95% CI: 1.648-2.219), and osmotic therapy (OR = 2.835, 95% CI: 1.871-5.102) were significantly correlated with early death of severe AIS. ROC curve analysis of the area under the curve after hospitalization showed that the maximum SOFA and ΔSOFA scores exceeded 0.7. CONCLUSION: Our study shows that urinary tract infection, mechanical ventilation, and osmotic therapy are risk factors for early death of severe AIS. The SOFA score has good predictive value for prognosis of severe AIS. These findings may provide a guideline for improving clinical outcome.

Effects of Fertility Behaviors on Depression Among the Elderly: Empirical Evidence From China.

Background: Increased population aging is associated with increased incidence of depression among the elderly. Existing studies have shown that ill-advised fertility behaviors during their youth also affect the health of the elderly. However, insufficient attention has been paid to depression among elderly in China. This paper focuses on how fertility behaviors affect senile depression among parents by examining the heterogeneity of such effects and tests the applicability of existing theoretical findings in a Chinese sample. Methods: The effects of fertility behaviors on depression among the elderly were investigated using the China Health and Retirement Longitudinal Study (CHARLS), a nationally representative dataset. The effects of early-age fertility behaviors on the degree of depression among the elderly were investigated using ordinary least squares and ordered probit models that adjusted for demographic and socioeconomic factors. Results: (1) The age of first childbirth, childbearing period, and number of births were significantly and positively correlated with the degree of depression among the elderly (particularly rural persons aged 50-70 and older womens). (2) Elderly persons with sons had no better mental health status than those without sons, thus indicating the inapplicability of the traditional concept of "more sons are equal to more happiness" to the actual mental health situation of the elderly in China today. Conclusion: Overall, multiple, late, and boy-oriented childbearing and overly long childbearing periods had negative effects on mental health among Chinese elderly persons. This study tested the applicability of existing theoretical inferences and empirical conclusions in China, thereby further expanding the current literature regarding the effects of fertility behaviors on depression among the elderly.

International Multisite Study of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes for Drug Proarrhythmic Potential Assessment.

To assess the utility of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) as an in vitro proarrhythmia model, we evaluated the concentration dependence and sources of variability of electrophysiologic responses to 28 drugs linked to low, intermediate, and high torsades de pointes (TdP) risk categories using two commercial cell lines and standardized protocols in a blinded multisite study using multielectrode array or voltage-sensing optical approaches. Logistical and ordinal linear regression models were constructed using drug responses as predictors and TdP risk categories as outcomes. Three of seven predictors (drug-induced arrhythmia-like events and prolongation of repolarization at either maximum tested or maximal clinical exposures) categorized drugs with reasonable accuracy (area under the curve values of receiver operator curves ∼0.8). hiPSC-CM line, test site, and platform had minimal influence on drug categorization. These results demonstrate the utility of hiPSC-CMs to detect drug-induced proarrhythmic effects as part of the evolving Comprehensive In Vitro Proarrhythmia Assay paradigm.